BR102020010073A2 - METHOD, SATELLITE GLOBAL NAVIGATION SYSTEM RECEIVER, AND, LEGIBLE STORAGE MEDIA BY NON-TRANSITIONAL COMPUTER - Google Patents

Abstract

a method is provided to acquire a signal from a satellite in a global satellite navigation system. the signal includes a pseudo-random code. the method includes, for each time period, a plurality of time periods: by generating signal samples, segments of the signal samples are correlated with a local copy of the pseudo-random code, thus producing correlation values for the time period. a discrete fourier transform is performed using, as inputs, the correlation values for the respective time period, thus producing a frequency representation of the correlation values for the time period. the frequency representations of the correlation values for the plurality of time periods are combined according to a data hypothesis. when a magnitude of the combined frequency representations meets predefined criteria, a frequency corresponding to the magnitude is selected as a tracking frequency for the satellite.

Description

METHOD, SATELLITE GLOBAL NAVIGATION SYSTEM RECEIVER, AND, LEGIBLE STORAGE MEDIA BY NON-TRANSITIONAL COMPUTER Related Orders

[001] This application claims priority to US Provisional Patent Application 62 / 851,004, filed on May 21, 2019, which is hereby incorporated by reference in its entirety.

Technical Field

[002] The modalities described refer, in general, to navigation systems that determine the position of a mobile object using navigation signals received from a plurality of satellites, and more methods and devices for acquiring signals from such satellites.

Fundamentals of the Invention

[003] Global satellite navigation systems (GNSS), such as GPS, GLONASS, Galileo and BeiDou, are used in many applications. In a GNSS system, each satellite transmits a signal that identifies the satellite and allows a receiver to determine the time at which the signal was sent. To do this, a GNSS satellite transmits a pseudo-random code (also called a pseudo-random noise code (PRN)). The pseudo-random code is, for example, a series of ones and zeros that appear random, but, in fact, uniquely identify the satellite. Using other data, such as ephemeris data and almanac data, which are encoded in the pseudo-random code using various modulation schemes (for example, BPSK, BOC), the receiver can determine the time at which the signal was sent. Using four or more satellites, the receiver can determine its position (for example, on Earth).

[004] For this process to work, the GNSS receiver must "acquire" the satellite signal. To acquire the signal, the GNSS receiver must determine several ambiguities, including the frequency of the received signal (for example, the frequency at which so-called “clippings” of the PRN code are received) and the offset from the PRN code (for example, the phase of the PRN code). Thus, acquiring the satellite signal includes, at a minimum, determining the correct frequency (for example, the clipping frequency) and code change (sometimes called a code shift) of the satellite signal, as received at the receiver . The conventional way to do this is by guesswork and verification: the receiver uses all possible “frequency hypotheses” and “code change hypotheses” until the correct combination is found.

[005] This process can be slow, especially for modern GNSS signals, which tend to use longer PRN codes, implying a greater number of chances of changing the code. In addition, some modern GNSS systems use types of modulation that require finer code changes (for example, BOC modulation compared to BPSK). For example, conventional systems may require 60 seconds to acquire a Galileo - E1B / E1C signal from each satellite, which has a cut length of 4,092 cutouts (compared to 1,023 for GPS - C / A) and a modulation scheme that requires twice the number of chances to change the code when compared to GPS - C / A.

[006] Thus, there is a need for systems and methods that can acquire GNSS satellite signals more quickly.

Brief Description of Drawings

[007] For a better understanding of the various modalities described, reference should be made to the Description of the Modalities below, together with the following drawings in which the same reference numbers refer to the corresponding parts throughout the figures.

[008] Figure 1 is a block diagram that illustrates a navigation system, according to some modalities.

[009] Figure 2 is a block diagram of a computer system, such as a computer system that is part of a mobile object navigation system, according to some modalities.

[0010] Figure 3 is a block diagram of a GNSS receiver, according to some modalities.

[0011] Figure 4 is a block diagram of an acquisition engine in a GNSS receiver, according to some modalities.

[0012] Figure 5 is a block diagram of a subsystem of an acquisition engine to add an offset in relation to a temporarily stored part of a PRN code sampled from a satellite signal, according to some modalities .

[0013] Figure 6 is a schematic diagram of a process for correlating a plurality of sample segments of a GNSS signal from a satellite with a local copy of the pseudo-random code for the satellite, according to some modalities.

[0014] Figure 7 is a schematic diagram of a process for carrying out discrete Fourier transforms (DFT) separated for different time periods of the GNSS signal from the satellite, according to some modalities.

[0015] Figure 8 is a schematic diagram of a sub-system to combine the results of the DFT for a plurality of time periods (for example, periods of PRN code) according to a data hypothesis, according to some modalities .

[0016] Figures 9A-9B illustrate the data hypothesis examples, according to some modalities.

[0017] Figures 10A-10B illustrate a flowchart of a method of acquiring a signal from a satellite in a global satellite navigation system (GNSS) and, more particularly, of acquiring a tracking frequency for the satellite. , according to some modalities.

[0018] Figures 11A-11D illustrate a flow chart of a method of acquiring a signal from a satellite in a global satellite navigation system (GNSS) and, more particularly, of acquiring a code change for the satellite , according to some modalities.

[0019] Figure 12 illustrates a flowchart of a method of acquiring signals from one or more satellites in a global satellite navigation system (GNSS) and, more particularly, of acquiring a tracking frequency and code change for each of several satellites (for example, for each satellite in view of the receiver), according to some modalities.

Summary of the Invention

[0020] Some modalities provide a system, computer-readable storage medium that stores instructions, or a method for acquiring a signal from a satellite in a global satellite navigation system (GNSS).

[0021] (A1) In some modalities, a method is performed on a global satellite navigation system (GNSS) receiver that includes one or more processors and instructions for execution by one or more processors. The method includes acquiring a signal from a satellite on a global satellite navigation system (GNSS). The signal includes a pseudo-random code for the satellite. The acquisition includes, for each respective period of time, a plurality of time periods: generating a plurality of samples of the signal; correlating a plurality of segments of the plurality of signal samples with a local copy of the pseudo-random code for the satellite, thereby producing a plurality of correlation values for the respective time period; perform a discrete Fourier transform (DFT) using, as inputs, the plurality of correlation values for the respective time period, thus producing a frequency representation of the correlation values for the respective time period; combining the frequency representations of the correlation values for the plurality of time periods according to a data hypothesis; and, according to a determination that a magnitude of the combined frequency representations of the correlation values for the plurality of time periods meets predefined criteria, select a frequency corresponding to the magnitude as a tracking frequency for the satellite. The method further includes determining a position of the GNSS receiver using the signal acquired at least in part by tracking the signal from the satellite using the tracking frequency.

[0022] (A2) In some modalities of (A1), each correlated segment of the plurality of signal samples corresponds to a duration of time. The plurality of signal samples is generated using a coarse frequency hypothesis. The method includes repeating the operations of generation, correlation, realization of the DFT and combination with the adjacent coarse frequency assumptions that are separated by a value less than or equal to the inverse of the time duration.

[0023] (A3) In some modalities of either (A1) - (A2), the generation of the plurality of signal samples includes: initially sampling the signal in an initial multiple of a frequency hypothesis; and decimating the signal initially sampled to produce the plurality of samples of the signal.

[0024] (A4) In some modalities of any of (A1) - (A3), the correlation of the plurality of segments of the plurality of signal samples with the local copy of the pseudo-random code for the satellite for each respective time period of the The plurality of time periods includes correlating n segments of the plurality of samples of the signal with the local copy of the pseudo-random code, where n is an integer greater than one. The DFT is a DFT of point m, where m is an integer greater than n. The realization of DFT includes using, as inputs, m— η zero values in addition to the n correlation values for the respective time period.

[0025] (A5) In some modalities of (A4), each correlated segment of the plurality of signal samples corresponds to a duration of time. An inverse of the duration of time divided by m is less than a frequency tolerance for tracking the satellite signal using the tracking frequency.

[0026] (A6) In some modalities of any of (A4) - (A5), the realization of DFT for a respective period of time from the plurality of time periods includes: using, as inputs, the n correlation values for the respective time period, in which the n correlation values are changed by n DFT entries compared to the n correlation values for a previous and adjacent time period of the plurality of time periods.

[0027] (A7) In some modalities of either (A1) - (A6), the correlation operations, realization of the discrete Fourier transform and combination are performed for each of a plurality of code change hypotheses.

[0028] (A8) In some modalities of any of (A1) - (A7), for a respective frequency hypothesis, the correlation operations, realization of the discrete Fourier transform and combination are performed for each of a plurality of satellites.

[0029] (A9) In some modalities of any of (A1) - (A8), the time period is a period of a complete instance of the pseudo-random code.

[0030] (B1) In addition, in some modalities, a method is performed on a global satellite navigation system (GNSS) receiver that includes one or more processors and instructions for execution by one or more processors. The method includes acquiring a signal from a satellite on a global satellite navigation system (GNSS). The signal includes a pseudo-random code for the satellite that has a predefined clipping length for a complete instance of the pseudo-random code. The acquisition includes: sampling the signal at a respective frequency; storing a first part of the sampled signal in a buffer, the buffer having a size that is less than the predefined clipping length sampled at the respective frequency; for each respective code change hypothesis from a plurality of code change hypotheses: correlate the first part of the sampled signal with a local copy of a part of the pseudo-random code to produce a correlation of the first part of the sampled signal with the local copy of the part of the pseudo-random code; and, according to a determination that the correlation of the first part of the sampled signal with the local copy of the part of the pseudo-random code for the respective code change hypothesis meets correspondence criteria, select the code change hypothesis for satellite tracking . The method further includes determining a position of the GNSS receiver using the signal acquired, at least in part, by tracking the satellite signal using the selected code change hypothesis.

[0031] (B2) In some modalities of (B1), the method additionally includes determining that none of the correlations for the plurality of code change hypotheses meet the correspondence criteria; storing a second part of the sampled signal in temporary storage, wherein the second part of the sampled signal is distinct from the first part of the sampled signal; for each respective code change hypothesis of the plurality of code change hypotheses: correlate the second part of the sampled signal with the local copy of a part of the pseudo-random code; and, according to a determination that the correlation of the second part of the sampled signal with the local copy of the part of the pseudo-random code for the respective code change hypothesis meets correspondence criteria, select the code change hypothesis for tracking the satellite.

[0032] (B3) In some modalities of (B2), the method additionally includes, before correlating the first part of the sampled signal with the local copy of a part of the pseudo-random code, temporarily storing the local copy of the part of the pseudo-random code. The correlation of the second part of the sampled signal with the local copy of the part of the pseudo-random code is performed without temporarily restoring the local copy of the part of the pseudo-random code.

[0033] (B4) In some modalities of any one of (B2) - (B3), the correlation of the first part of the sampled signal with the local copy of the part of the pseudo-random code for each respective hypothesis of code change of the plurality of hypotheses code change comprises a first iteration of a plurality of temporary storage change iterations. The correlation of the second part of the sampled signal with the local copy of the part of the pseudo-random code for each respective code change hypothesis of the plurality of code change hypotheses comprises a second iteration of the plurality of temporary storage change iterations. The method additionally includes: according to a determination which exhaustion criteria, in relation to the signal sampling using the respective frequency, were satisfied: resampling the signal at a second frequency different from the respective frequency; storing a third part of the signal sampled at the second frequency in the temporary storage; for each respective code change hypothesis of the plurality of code change hypotheses: correlate the third part of the signal sampled in the second frequency with the local copy of the part of the pseudo-random code; and, according to a determination that the correlation of the third part of the signal sampled at the second frequency with the local copy of the part of the pseudo-random code for the respective code change hypothesis meets matching criteria, select the code change hypothesis for tracking of the satellite.

[0034] (B5) In some modalities of (B4), the exhaustion criteria include a criterion that is met when a maximum number of temporary storage change iterations has been exhausted without selecting a code change hypothesis for the satellite.

[0035] (B6) In some modalities of either (B2) - (B5), the method additionally includes adding an offset in relation to the hypothesis of changing the code for tracking the satellite based, at least in part, on a displacement between the first part of the sampled signal and the second part of the sampled signal.

[0036] (B7) In some modalities of either (B1) - (B6), the method additionally includes acquiring a second signal from a second satellite in a second global satellite navigation system (GNSS) distinct from the system global satellite navigation. The second signal includes a second pseudo-random code for the second satellite that has a predefined second clipping length. The temporary storage has a size that is larger than the second predefined clipping length sampled at the respective frequency.

[0037] (B8) In some modalities of (B7), the acquisition includes: for each respective code change hypothesis of the plurality of code change hypotheses: correlate the first part of the sampled signal with a local copy of a part of the second pseudo-random code; according to a determination that the correlation of the first part of the sampled signal with the local copy of the part of the second pseudo-random code for the respective code change hypothesis meets the correspondence criteria, select the code change hypothesis for tracking the second satellite.

[0038] (B9) In some modalities of either (B1) - (B8), the respective frequency is an integral multiple of a frequency hypothesis.

[0039] In some modalities, a global satellite navigation system (GNSS) receiver is provided that includes one or more processors; and memory storage instructions that, when executed by a global satellite navigation system (GNSS) receiver that includes one or more processors, cause the GNSS receiver to perform any of the methods described here.

[0040] In some modalities, a global satellite navigation system (GNSS) receiver is provided that includes one or more processors and means to perform any of the methods described here.

[0041] In some modalities, a non-transitory computer-readable storage medium is provided that stores instructions that, when executed by a global satellite navigation system (GNSS) receiver that includes one or more processors, make the GNSS receiver perform o any of the methods described here.

Description of Modalities

[0042] Figure 1 is a block diagram illustrating a navigation system 100, according to some modalities. The navigation system 100 enables a mobile object 110 (for example, a telephone, specialized GNSS receiver, a boat, a truck or other vehicle, an agricultural tool, mining tool, drilling system, etc.) to determine, at any its current position 112 in relation to a global coordinate system (for example, a coordinate system for Earth 114). The movable object 110 is equipped with a satellite receiver (navigation signal receiver 120), typically including or coupled to one or more satellite antennas 140, to receive satellite navigation signals from at least four satellites 115 that are orbiting the Earth. The satellite navigation signals received by the mobile object 110 are typically signals from the global satellite navigation system (GNSS). Tables 1-2 below provide examples of GNSS signals from exemplary GNSS systems.

[0043] In Tables 1-2 exposed, the signal type refers to the various signals provided by the various GNSS systems (for example, GPS-C / A is the bulk GPS acquisition signal), PRN period is the duration of time for a complete instance of the PRN code (in milliseconds), T is the length of time, in milliseconds, during which a single bit of data is encoded (in milliseconds), and is also the minimum length of time between value transitions of the signal due to either secondary code modulation (SC) or data modulation or both, the length of PRN is the number of cutouts in a complete instance of the PRN code, and the cutout rate is the rate at which the cutouts are transmitted (in millions of clippings per second (MCPS)). The rate at which clippings are transmitted may differ from the rate at which they are received based, for example, on the Doppler effect and other effects. The minimum length, in milliseconds, shown in Table 2 is the minimum value of sampled data needed, for each type of signal, to ensure that the receiver can detect the start of a PRN sequence for this type of signal. For signal types where the minimum length is greater than the available sample buffer memory, the receiver uses an iterative technique, described in detail below, to locate the start of a PRN sequence and thus determine the phase of the signal received from a particular satellite.

[0044] The movable object 110 also receives satellite orbit correction information and satellite clock correction information (sometimes collectively called "correction information") for the plurality of satellites. Correction information is typically broadcast by and received from one or more satellites 118 other than GNSS 115 satellites, using an antenna 142 and a signal receiver 152 (see figure 2) other than antenna 140 and receiver 150 used for receive satellite navigation signals. However, in some modalities, the same antenna and receiver are used to receive both satellite navigation signals and correction information.

[0045] The moving object 110 determines a moving object position 110, using the satellite navigation signals received and the satellite orbit correction information and the satellite clock correction information received for the plurality of satellites. In some embodiments, the received satellite navigation signals are processed by the navigation signal receiver 120, including an analog signal processing circuitry system 122 and a digital signal processor 124, taking into account the correction information, to determine code measurements and phase measurements for signals received from four or more satellites 115. The built-in computer system 130 determines the position of moving object 110 based on these measurements.

[0046] Figure 2 is a block diagram of the computer system 130 in, and used by, a moving object to determine the position of the moving object, according to some modalities.

[0047] Computer system 130 typically includes one or more processors (sometimes called CPUs, hardware processors) 202 to execute programs or instructions; memory 210; one or more communications interfaces 206; and one or more communication buses 205 to interconnect these components. Computer system 130 optionally includes a user interface 209 comprising a display device 211 and one or more input devices 213 (for example, one or more of a keyboard, a mouse, a touch screen, a numeric keypad, etc.) coupled to other components of computer system 130 by one or more communication buses 205. The navigation signal receiver 150, and complementary receiver (s) 152, if provided, are also coupled in other components of the computer system 130 by one or more communication buses 205. The one or more communication buses 205 may include a circuit system (sometimes called a set of cutouts) that interconnects and controls communications between the components of the system.

[0048] The communication interface 206 (for example, a receiver or a transceiver) is used by computer system 130, and, more generally, by mobile object 110, to carry information to external systems, and to receive information. communications from external systems.

[0049] Memory 210 includes high speed random access memory, such as DRAM, SRAM, DDR RAM or other solid state random access memory devices; and may include non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid state storage devices. Memory 210 optionally includes one or more storage devices located remotely from the CPU (s) 202. Memory 210, or, alternatively, the non-volatile memory device (s) in memory 210, comprises a computer-readable storage medium. In some embodiments, memory 210 or the computer-readable storage medium of memory 210 stores the following programs, modules and data structures, or a subset of them:
* an operating system 212 that includes procedures for handling various basic system services and for performing hardware-dependent tasks;
* a communications module 214 that operates in conjunction with communication interface 206 (for example, a receiver and / or a transceiver) to handle communications between the mobile object 110 and external systems 160 (figure 1); the connection between computer system 130 and external systems 160 may include a communication network 162, such as the internet or a public or proprietary wireless network;
* a user interface module 216 for receiving the information from one or more input devices 213 of the user interface database 209, and for carrying the information to a user of the movable object 110 via one or more display or output devices 211;
* a navigation module 218 for determining a position of the moving object;
* an acquisition engine 220 for acquiring satellite signals from GNSS satellites, including determining a tracking frequency and a code change (sometimes called a code shift) for each of several respective GNSS satellites;
* a 222 tracking module, sometimes called a satellite signal tracking module, which tracks GNSS satellite signals using the acquisition information (for example, the tracking frequency and code change) transferred from the module acquisition 220. For example, in some modalities, the tracking module 222 samples (for use by the navigation module 218) a signal from the GNSS satellite using a tracking frequency and code change determined by the acquisition module 220.

[0050] The operating system 212 and each of the aforementioned modules and applications corresponds to a set of instructions to perform a function described above. The instruction set can be executed by one or more processors 202 of the computer system 130. The above-identified modules, applications or programs (ie instruction sets) do not need to be implemented as separate software programs, procedures or modules, and thus , several subsets of these modules can be combined or otherwise rearranged in various modalities. In some embodiments, memory 210 stores a subset of the modules and data structures identified earlier. In addition, memory 210 optionally stores additional modules and data structures not described above.

[0051] It is intended that figure 2 is more as a functional description of the various resources that may be present in a computer system 130 of a mobile object 110 than as a structural schematic representation of the modalities described here. In practice, and as recognized by those skilled in the art, the items shown separately can be combined and some items can be separated. For example, some items shown separately in figure 2 can be combined into a single module or component, and individual items can be implemented using two or more modules or components. The actual number of modules and components, and how resources are allocated between them, will vary from one implementation to another.

[0052] Furthermore, in some modalities, some or all of the functions described above can be implemented with hardware circuits (for example, which can comprise graphics processors for the efficient realization of discrete Fourier transforms (DFTs), field programmable ports (FPGAs), application-specific integrated circuits (ASICs), a “cut-out system” that includes processors and memory, or the like). To this end, in some embodiments, CPUs 202 include specialized hardware to perform these and other tasks. In some embodiments, these operations are performed by the navigation signal receiver 150/152 instead of the computer system 130.

[0053] Figure 3 is a block diagram of a GNSS 300 receiver, according to some modalities. An antenna 140 receives a GNSS signal from a satellite (for example, satellite 115, figure 1). In some embodiments, antenna 140 receives a GNSS signal from each of a plurality of satellites (for example, four or more satellites in a respective satellite constellation). In some embodiments, antenna 140 receives a GNSS signal from a plurality of satellites from a plurality of different constellations (for example, it receives GPS signals, GLONASS signals, and / or BeiDou signals). Thus, in some modalities, the GNSS 300 receiver is a multi-frequency multi-constellation receiver (MCMF). The signals received from antenna 140 are amplified by a low noise amplifier 304 and passed to both a high frequency channel 301a and a low frequency channel 301b.

[0054] Channels 301a and 301b include the analog processing circuit system 306a and 306b, respectively. In some embodiments, the analog processing circuit system 306a includes a high-frequency (RF) to intermediate frequency (IF) analog chain, which may include one or more filters and a variable gain amplifier. In some embodiments, the analog processing circuit system 306b includes an analog low-frequency (RF) to intermediate frequency (IF) chain, which may include one or more filters and a variable gain amplifier.

[0055] Channels 301a and 301b include analog to digital converters (ADC) 308a and 308b, respectively. In some embodiments, ADCs 308a and 308b sample the GNSS signal at a first sampling rate (for example, 40.92 MHz). In some embodiments, the first sampling rate is a multiple (for example, an integral multiple) of a clipping rate for the GNSS signal.

[0056] Channels 301a and 301b include a digital processing circuit system 310a and 310b, respectively. In some embodiments, the digital processing circuit system 310a and 310b includes selective digital band or subband filtering.

[0057] Channels 301a and 301b are passed both to a GNSS 314 satellite tracking engine (for example, through the band selection multiplexer (MUX) 312) and to a GNSS 316 satellite acquisition engine, which is described in detail below. For now, suffice it to say that the GNSS 316 satellite acquisition engine determines the parameters needed by the GNSS 314 satellite tracking module for tracking satellites, such as a code change and a frequency (for example, clipping frequency). Furthermore, the pseudo-range information (for example, measurements of the distance between receiver 300 and each satellite in a set of four or more satellites that are in view of receiver 300) determined by the GNSS 314 satellite tracking engine is the which is used to determine the location of the receiver 300.

[0058] Figure 4 is a block diagram of a 316 acquisition engine in a GNSS receiver, according to some modalities. In some embodiments, the acquisition engine 316 includes the subcomponents described below.

[0059] A subband selection module 402 selects the digital signal of the band corresponding to a signal from the satellite that the acquisition engine 316 is trying to acquire.

[0060] A mixer 404 performs downward conversion of the signal to a base band frequency (for example, removes a signal from the carrier). In some circumstances, the baseband signal produced by mixer 404 is referred to here as an “initially sampled signal” and comprises a digital signal sampled at the first sampling rate, as described above (for example, roughly 40 MHz).

[0061] A numerically controlled oscillator (NCO) 406 provides an intermediate frequency signal for the mixer 404 so that the mixer 404 can perform the downward conversion of the signal to the baseband frequency (for example, clearing the signal from the carrier frequency ). In some embodiments, the NCO 406 is sufficiently tunable (for example, using the frequency displacement module 408) to cover the uncertainty in the frequency of the satellite signal (for example, the inverse of the clipping rate) resulting from oscillator errors a edge and line of sight (LOS) movement (for example, +/- 10 KHz). In addition, some GNSS systems, such as GLONASS, shift the frequencies of different satellite signals (for example, GLONASS signals are shifted from each other at approximately 500 KHz intervals). In some embodiments, when performing a frequency search (for example, as described in relation to method 1000, figures 10A-10B), the frequency displacement module 408 adjusts the frequency of NCO 406 in frequency hypothesis steps predefined, which can be controlled by a lookup table.

[0062] A frequency displacement module 408 configures (for example, defines) the frequency of the intermediate frequency signal produced by NCO 406.

[0063] A decimator 410 decimates the signal initially sampled to produce a decimated signal at a decimated rate. For example, in some embodiments, decimator 410 discards 90% of the signal initially sampled (for example, in such a way that the decimated signal has an effective sampling rate of 4.092 MHz instead of roughly 40 MHz). In some embodiments, the decimator 410 includes a low pass filter (for example, a finite impulse response filter (FIR) or an infinite impulse response filter (IIR)). Such a filtering process mitigates aliasing noise caused by decimation.

[0064] A quantization module 412 quantizes the signal decimated over L levels (for example, where L is an integer). For example, the quantization module 412 converts the decimated signal values to one of a predefined plurality of L quantized values (for example, when L = 2, the quantization module 412 converts the sampled signal (for example, samples of the acquired signal ) in decimated signal values, each having a value of 0 or a value 1; in another example, L = 3, in which case the quantization module 412 converts the acquired signal samples into decimated signal values, each having a value of 1, 0 or -1). The quantization module 412 thus reduces the value of sample memory 414 required to store a portion of the sampled signal. It is noticed that the signal acquisition is less sensitive to quantization errors than the signal tracking.

[0065] A sample memory 414 stores a temporarily stored portion of a sampled decimated satellite signal (for example, at least a portion of the quantized decimated sample signal received from one or more satellites). As described in more detail below, in some modalities, or in some circumstances, the stored portion of the decimated quantized sample signal corresponds to less than the full portion of a PRN code instance used by a particular satellite (for example, or less than twice the full PRN code instance for the satellite). In some embodiments, sample memory 414 is large enough to store twice the length of a medium-length PRN code (for example, such as a PRN code from a Galileo E1B / E1C signal). The modalities described below provide different ways of determining a code change, depending on whether the sample memory 414 has a size that is greater than or less than twice the length of the satellite's PRN code whose signal is being acquired (thus , depending on what type of satellite signal is being acquired).

[0066] A PRN 416 local sequence memory stores local copies (for example, sometimes called replicas) of the PRN codes for the respective satellites or stores the parameters necessary to generate the PRN codes for the respective satellite. For example, the PRN location sequence memory stores the PRN codes (or the values needed to generate the PRN codes) for each satellite in each constellation for which the acquisition engine 316 can attempt to acquire a signal from the satellite. In some embodiments, the stored (or generated) PRN codes are versions of the PRN codes corresponding to the decimated frequency (for example, a GPS-CA signal, with a PRN length of 1,023 clippings and a clipping rate of 1,023 MHz will have 4,092 values long with a sampled rate of 4.092 MHz). In some embodiments, for reasons that will become clear when considering the correlation processes described below, the sequence memory of the PRN site 416 stores (or generates) the PRN codes with a length corresponding to half the size of the sample memory 414 (for example, regardless of the actual length of the entire PRN code instance). PRN codes locally stored or generated in memory 416 are, in some cases, for long PRN codes (for example, PRN codes with 10,230 clippings, transmitted over a period of 10 ms), shorter than the corresponding full PRN code used by respective satellite.

[0067] A processing module 418 performs several operations described in relation to method 1000 (figures 10A-10B) and / or method 1100 (figures 11A-11D). For example, in some embodiments, processing module 418 correlates the PRN code for a satellite, which is stored in the sequence memory of the PRN location, with the portion of the signal sampled in sample memory 414, to determine a code change (sometimes called a code shift) and frequency for the satellite.

[0068] A control module 420 controls these and other components.

[0069] In some modalities, the subband selection processing module 402, the mixer 404 and the NCO 406 operate at a clock rate corresponding to the first sampling rate (for example, roughly 40 MHz).

[0070] In some embodiments, the decimator 410, the quantization module 412 and the sample memory 414 operate at a clock rate corresponding to the decimated sample rate (for example, 4.092 MHz).

[0071] It should be noted that the temporarily stored portion of the PRN code sampled from the satellite signal stored in sample memory 414 may include all forms of other information and noise, such as PRN codes from other satellites (for example , in addition to the satellite being acquired) and one or more data signals for the satellite that are acquired, as well as data signals from other satellites. Thus, as used herein, the term "temporarily stored part of the PRN code sampled from the satellite signal" means a part of a signal that includes the PRN code from the satellite signal.

[0072] In some modalities, the frequency decimated depends on the clipping rate of the PRN code, as well as the type of modulation. In some modalities, for BPSK modulation, the GNSS 316 acquisition engine identifies the V-code change of a clipping, so that the frequency decimated is at least twice the clipping rate. In some modalities, when acquiring a signal from the satellite that uses BOC modulation, because the loss of autocorrelation is significantly worse (for example, 3 times worse than for BPSK modulation), a frequency decimated to four times the rate of clipping is employed.

[0073] Figure 5 is a block diagram of a subsystem 500 of an acquisition engine to add an offset from a temporarily stored part of a PRN code sampled from a satellite signal, according to some modalities.

[0074] As noted earlier, in some modalities, and in some circumstances (for example, depending on the GNSS signal that is acquired), the sample memory 414 is large enough to test all possible chances of changing the code without resampling and temporary signal re-storage. For example, as long as the sample memory 414 is large enough to store at least two complete instances of the PRN code for the satellite being acquired, the PRN code is guaranteed to start and end at the temporarily stored part.

[0075] However, the storage of two complete instances of the PRN code may be impractical for satellite signals with long PRN codes. For example, the BeiDou B1C signal has a cut-out length of 10,230 cut-outs and uses BOC modulation, implying the need for long temporary storage if twice the length of PRN (at the sampled frequency) needs to be stored. In such situations, it is often more practical to store a portion of the decimated signal that is less than twice the length of PRN. Doing this means that, for the temporarily stored part of the signal, all selected code change hypotheses may fail, in which case the signal is collected (for example, resampled and temporarily re-stored) with an offset (compared to the part initially temporarily stored the signal) and the chances of changing the code are retained.

[0076] The subsystem 500 provides a simple solution for sampling different parts of a satellite's PRN code through successive iterations of changing the temporary storage. For this purpose, for each temporary storage offset iteration, an offset is added to the temporarily stored portion of the PRN code sampled from a satellite signal (for example, and stored in sample memory 414). In some modalities, the displacement corresponds to an integer number of milliseconds, when compared to the sample of the GNSS signal previously collected.

[0077] Subsystem 500 requires knowledge only of the full period of an instance of the PRN code (TPRN) of the signal being acquired and the length of the temporary storage. Given these two parameters, subsystem 500 ensures that a corresponding part of the sampled PRN code will be stored in sample memory 414 in a reasonable number of maximum temporary iteration changes. For example, a sample memory 414 stores 8 ms of the sampled signal (for example, at the decimated rate) and will have a corresponding part of the PRN code in eight (indexing from 0 to 7) iterations for a BeiDou B1C or GPS L1C signal that has a PRN code with 10,230 clippings. The 500 subsystem is easy to implement on hardware (for example, using an ASIC) and requires very little processing time. In some modalities, when the maximum number of temporary storage change iterations is exhausted without identifying a code change, the GNSS 316 satellite acquisition engine (figure 3) moves to a different frequency hypothesis.

[0078] Sub-system 500 includes a counter 502 that accompanies a phase of a decimated signal from decimator 410. In some embodiments, counter 502 is a submisecond counter. For example, in some modalities, counter 502 counts time steps (for example, phase changes) in the decimated rate, which satisfies the maximum necessary clipping rate for any constellation for which the GNSS 316 satellite acquisition engine can acquire a signal (for example, BeiDou B1I has the fastest clipping rate, at 2.046 MHz of any GNSS signal currently implemented, and thus, in some modalities, counter 502 counts the time steps at a rate of 4.092 MHz) .

[0079] Subsystem 500 includes a counter 504 (for example, a second counter) that accompanies a millisecond phase shift associated with the processing time by the GNSS 316 satellite acquisition system. In some embodiments, the counter 504 is a millisecond counter that counts the time shift in milliseconds (for example, it has the effect of calculating a phase that is a ceiling function of the processing time for processing a PN sequence).

[0080] Subsystem 500 includes an adder 506 that adds the outputs of counter 502 and counter 504 and provides the result as an index 507 to sample memory 414. Index 507, sometimes called the temporary storage index current, is equal to counter value 502 plus counter value 504, and indicates the address in memory 414 where subsystem 500 stores the current decimated sample (for example, sample memory 414 stores the current sample at the address defined by index 507).

[0081] When the GNSS 300 receiver is being used to acquire navigation signals that have a minimum length (see Table 2), equal to two integral PRN sequences, which is greater than the capacity of the sample memory 214, the receiver 300 performs multiple iterations of storing data samples in sample memory 414 and analyzing this data, until either of the two integral PRN sequences of the signal has been acquired and analyzed, or the phase of the signal has been determined. As a result, even navigation signals with long PRN sequences can be acquired using a fixed-length sample memory that is less than the longest “minimum length” of sampled data that may be required to detect the start phase of the PRN sequence in these signals.

[0082] In some modalities, to avoid collecting signal samples from any part of a PRN sequence that has already been collected and analyzed, without locating the beginning of the PRN sequence in the sampled signal, subsystem 500 verifies this condition using logic decision module 512, and, if the condition is met, the start of the new signal sampling iteration is delayed by a predefined time value, such as a millisecond, which is equivalent to advancing the next iteration phase data sampling by this predefined time value (for example, 1 millisecond), compared to a previous iteration. To this end, subsystem 500 includes a logic module 508 that enables a module counter 510 when signal sample collection (for example, for a particular frequency hypothesis, as discussed below) begins. The module counter 510 measures the processing period in milliseconds against the PRN sequence period in milliseconds (for example, it determines the module of the processing period in relation to the PRN sequence period), the result of which is used by a decision unit 512 for decide whether to postpone the next signal sample collection for the preset time value (for example, 1 millisecond). If the condition tested by decision unit 512 is met, the delay of the next signal sample collection by the predefined time value avoids collecting signal samples for a part of the PRN sequence that has already been collected and analyzed. If the condition tested by decision unit 512 is not met, the PRN phase of the signal samples that are currently produced by decimator 410 is different from that of the previous iteration (s), and therefore the storage of the signal samples in sample memory 414 proceed without first waiting for the predefined time value to elapse. In some embodiments, other mechanisms and methods are used to ensure that signal samples corresponding to all parts of a PRN sequence are temporarily stored and analyzed, through multiple collection and analysis iterations, during the processing of satellite signals whose sequences PRN are long enough that the signal samples for two integral PRN sequences cannot all be stored in the sample memory at the same time.

[0083] Figure 6 is a schematic diagram of a process 600 for correlating a plurality of segments 606 of samples of a GNSS signal from a satellite with segments 604 (for example, 604a to 604p) of a local copy of the pseudo-random code for the satellite (for example, stored or generated by the sequence memory of the PRN 416 site), according to some modalities. Segments 604 are sometimes referred to as code segments, PRN code segments, or PRN sequence segments, all of which have the same meaning. In process 600, for each of a plurality of time periods 602 (e.g., adjacent time periods 602a through 602d), a plurality of segments 604 of a local PRN sequence are correlated (for example, using a correlator 610) with corresponding segments 606 in a first offset from the result in a first set of correlations. Then, the second segments 608 of the samples of the GNSS signal from the satellite, which are changed in 1 sample in relation to the first segments 606, are correlated with the local replica segments 604 to generate a second set of correlations. Such change and correlation continues until testing of a predefined hypothesis has been completed (for example, segments 604 of the local PN sequence are correlated with the sampled signal 606 according to the code shift hypothesis that is tested).

[0084] In some embodiments, the local copy of the pseudo-random code for the satellite is half the length of the temporarily stored part of the PRN code sampled from the satellite signal (for example, stored in sample memory 414), so that the local copy can be moved up to half the length of temporary storage. Note, however, that the local copy of the pseudo-random code for the satellite does not need to represent the full one instance of the pseudo-random code since, in some circumstances, the full one instance of the pseudo-random code is longer than the sample memory 414 .

[0085] In some circumstances, time periods 602 correspond to the shortest intervals in which a data signal or secondary code (for example, at the top of the PRN code) can change value (for example, turn from a value “0 ”To a“ 1 ”value or a“ 1 ”value to a“ 0 ”value). For example, in relation to Tables 1-2, each GNSS system currently implemented encodes data in an integral multiple of time periods in milliseconds (for example, the data period for GPS-CA is 20 ms, the data period for GAL-E1B is 4 ms). Thus, without knowing the phase of the data signal, the best that can be said is that the data signal can change its value in any millisecond delimitation. The effect of the data signal changing value is to change the PRN code parity. Thus, in some modalities, the 602 time periods are chosen as milliseconds, so that the frequency shift and code shift hypothesis can be performed without regard to the data pattern (for example, by combining the correlations of different periods 602 using different possible data patterns, each of which is referred to here as a “data hypothesis”).

[0086] Thus, in some embodiments, time periods are milliseconds (for example, time period 602a is a millisecond, time period 602b (not shown) is a millisecond, time period 602c (not shown) is a millisecond, and the 602d time period is a millisecond). In some embodiments, each of the plurality of segments 604 corresponds to a quarter of the time period 602 (for example, when each time period 602 is a millisecond, each segment 604 corresponds to a quarter of a millisecond). Thus, a first code change hypothesis results from the correlation between the first quarter of the 606 millisecond segments of the sampled signal with the corresponding fourth quarter of the 604 millisecond segments of the local copy of the PRN sequence; a second code change hypothesis results from the correlation between the second quarter of the 608 millisecond segments of the sampled signal with the corresponding fourth location of the 604 millisecond segment of the local copy of the PRN sequence; etc.

[0087] In some embodiments, correlators 610a through 610p (whose correlators 610a-610d and 610o-610p are shown in figure 6) are physically incorporated as the same correlator (for example, the same hardware is used multiple times to compute the values correlation 612a to 612p). In some embodiments, correlators 610a through 610p are physically incorporated as a plurality of correlators (for example, a set of correlators).

[0088] In some embodiments, the correlation of each segment 604 of the local copy of the PRN sequence (for example, using a 610 correlator) with the corresponding signal samples of segments 606 in the first code change (corresponding to a first change hypothesis) code) produces a first correlation value 612 for the first code change hypothesis; correlating each segment 604 of the local copy of the PRN sequence with the signal samples in a second code change, represented in figure 6 by segments 608 of the sampled data, produces a second correlation value 612 for the second code change hypothesis; and, similarly, correlations performed using third and fourth code change hypotheses produce third and fourth correlation values 612. Thus, a plurality of correlation values 612 (for example, 612a to 612p) is produced for each respective time period 602 (for example, correlation values 612a-612d are produced for time period 602a from segments 604a-604d).

[0089] Figure 7 is a schematic diagram of a 700 process for carrying out discrete Fourier transforms (DFT) for the 612 correlations produced for different code change hypotheses, described in relation to figure 6, according to some modalities . The DFT 700 process is used to produce a combined frequency representation of the GNSS signal from the separate DFTs. To this end, the separate DFTs for the individual 602 time periods (for example, millisecond periods) are combined according to possible data pattern hypotheses and one of the resulting combined frequency representations is selected (based on predefined criteria) such as the combined frequency representation (for example, combined frequency representation 804, figure 8).

[0090] From the combined frequency representation of the GNSS signal, a tracking frequency for the GNSS signal is selected. However, it is realized that the DFT 700 process produces a frequency representation that covers a frequency range, and the tracking frequency can fall outside this frequency range. To this end, in some embodiments, the DFT 700 process is performed iteratively using a plurality of coarse-frequency assumptions (for example, using coarse-frequency steps of 2 kHz). For example, for a currently selected code change hypothesis, the DFT 700 process is performed iteratively to cover all frequencies that can potentially be associated with the GNSS signal (for example, for a particular satellite) that the receiver is trying to acquire, and the resulting strongest combined frequency representation 804, for all these iterations, is then compared to the predefined criteria to determine whether the signal was, in fact, acquired.

[0091] In the example shown in figure 7, each calculation of DFT 704 has 32 entries (of which only 16 are shown in figure 7, due to space restrictions). Of these 32 entries, four are correlation values produced for a corresponding period of time, and the others are zero values.

[0092] In process 700, a first calculation of DFT 704a is performed using correlation values 612a-612d from a first period of time 602a (for example, as inputs) to produce a frequency representation 702a of correlation values 612a-612d for the first time period 602a; a second calculation of DFT 704b is performed using the 612e-612h correlation values from a second time period 602b (for example, adjacent to and after the first time period 602a) to produce a 702b frequency representation of the correlation values 612e-612h for the second time period 602b (for example, correlation values 612e-612h are changed by 4 entries in relation to the calculation of DFT 704a); a third calculation of DFT 704c is performed using the correlation values 612i-612l from a third time period 602c (for example, adjacent to and after the second time period 602b) to produce a frequency representation 702c of the correlation values 612i-612l for the third time period 602c (for example, correlation values 612l-612i are changed by 4 entries in relation to the calculation of DFT 704b); and a fourth calculation of DFT 704d is performed using the 612m-612p correlation values from a third time period 602d (for example, adjacent to and after the third time period 602c) to produce a 702d frequency representation of the values of 612m-612p correlation for the third 602d time period (for example, 612m-612p correlation values are changed by 4 entries in relation to DFT 704c calculation).

[0093] Note that, although DFT 704 calculations are performed separately, in some modalities, DFT calculations are performed by the same hardware (for example, performed serially). In some modalities, the calculation of DFT 704 is performed by separate hardware (for example, performed in parallel). As well as, in some embodiments, to refine the frequency resolution, additional zero inputs are provided for the DFT 704 calculations to further reduce the frequency uncertainty of the produced frequency representations 702.

[0094] Additionally, some of the characteristics of the DFT calculations bear mention, in particular, the number of inputs used for calculating the DFT and the temporal length of the 604 segments (figure 6) that are used to generate the 612 correlation values. As noted earlier, the GNSS acquisition engines described here use only the coarse frequency steps to test the frequency assumptions. For example, in some modalities, the NCO 406 shifts adjacent frequency assumptions in 2 kHz steps. The purpose of the acquisition engine 316 (figures 3-4) is to transfer a tracking frequency that is at a tracking threshold of the tracking engine 314 (figure 3). For example, in some embodiments, the tracking motor 314 can track signals (for example, through phase locking) if the tracking frequency provided by the acquisition motor 316 is at 62.5 Hz (125 Hz / 2) of frequency of the GNSS signal that is received from the GNSS satellite whose signal is being acquired.

[0095] In some modalities, the frequency range covered by DFT 704 calculations is equal to the inverse of a quarter of a millisecond, 4 kHz. In modes in which a 32-point DFT is used, the frequency uncertainty is half the size of the frequency position, measured in Hz, at 4,000 Hz / 32 = 125 Hz. But the 2 kHz coarse frequency uncertainty is 4 dB . To mitigate the power degradation resulting from the thick frequency uncertainty, the range of frequencies covered by the DFT calculations can be reduced to 2 kHz from 4 kHz, reducing the thick frequency uncertainty by a factor of two, and resulting in a 0.9 dB power degradation.

[0096] Note that, in an alternative approach, all 612a-612p correlation values are applied to the same DFT calculation 704 (for example, as inputs). The various data hypotheses can be tested by repeating this DFT calculation according to different possible data hypotheses (for example, by changing the parities of certain entries, depending on the data hypothesis). However, because DFTs are a computationally costly exercise, while the linearity that combines the outputs of the DFTs is not, it is more efficient to perform separate DFTs for the different time periods 602 (for example, and to fill in the remaining entries in the calculation of the DFT 704 with zero values), then combined frequency representations 602 according to the different possible data hypotheses.

[0097] Each point (for example, each exit point) of frequency representations 702 corresponds to a "frequency level" that has a frequency range equal to the frequency range covered by DFT 704 calculations divided by the total number of points used by DFT calculations 704. Furthermore, the frequency range covered by each point of frequency representations 702 must correspond to a frequency range that is no greater than the crawl limit for crawler 314. Thus, as an example, using the quarter of the 604 millisecond segments in a 32-point DFT implies that each point in the frequency representations 702 corresponds to a 125 Hz “level” (frequency range) that is equal to the exemplary tracking limit above. In some modalities, DFT 704 calculations transmit magnitudes for half of the frequency positions, for example, the 16 middle positions of the 32 positions, for which the magnitudes can potentially be generated, and it is these magnitudes that are combined by the methodology shown in figures 8 and 9A-9B.

em que:
* k ∈[0,M-1] é o número da posição para o valor de saída da DFT que é computado;
* M=2R/V é o número de pontos da DFT (posições de saída), que é igual ao número de entradas em cada computação da DFT, incluindo 1/V valores de correlação e M - 1/V valores de ponto zero;
* R é o comprimento, em milissegundos, dos dados amostrados que são processados durante cada iteração do processamento de amostragem e análise;
* V é o número de hipóteses de mudança de código que serão testadas por milissegundo dos dados de sinal amostrados;
* M0= 1/V é o número de pontos de correlação por milissegundo dos dados de sinal amostrados;
* corr(i) é o i-ésimo valor de correlação; por exemplo, no exemplo da figura 6, há quatro (M0 = 4) valores de correlação 612 (por exemplo, 612a-612d) produzidos para cada milissegundo de dados de sinal amostrados; e
*D [i/M0] é o bit dos dados (desconhecidos) através do período submilissegundo (SubmS) identificado pelo índice i. O valor do bit dos dados é constante para cada somatória de M0. Da forma descrita em outro local neste documento, a computação da DFT é realizada de forma que os quatro componentes da DFT para cada posição de saída possam ser somados de acordo com cada possível padrão de dados.[0098] A mathematical representation of the DFT calculations represented by the DFT 700 process in figure 7 is as follows:

on what:
* k ∈ [0, M-1] is the position number for the DFT output value that is computed;
* M = 2R / V is the number of DFT points (output positions), which is equal to the number of inputs in each DFT computation, including 1 / V correlation values and M - 1 / V zero point values;
* R is the length, in milliseconds, of the sampled data that is processed during each iteration of the sampling and analysis processing;
* V is the number of code change hypotheses that will be tested per millisecond of the sampled signal data;
* M0 = 1 / V is the number of correlation points per millisecond of the sampled signal data;
* corr (i) is the i-th correlation value; for example, in the example in figure 6, there are four (M0 = 4) correlation values 612 (for example, 612a-612d) produced for each millisecond of sampled signal data; and
* D [i / M0] is the data bit (unknown) through the submisecond period (SubmS) identified by index i. The data bit value is constant for each sum of M0. As described elsewhere in this document, DFT computation is performed so that the four components of DFT for each output position can be added according to each possible data pattern.

[0099] In some modalities, such as the example shown in figure 7, V = 0.25, R = 4, M = 32, and Mo = 4 were chosen. The use of the DFT technique filled with zero point described here reduces the frequency uncertainty to 250 / R Hz (for example, 62.5 Hz), thus reducing the loss of timing to 0.9 dB. The equation shown above is for a m-point DFT that can be divided into R (for example, 4) m-point DFTs that each have a small number of non-zero inputs. Since only a small part of the inputs (for example, 4 out of 32) inserted in the m-point DFTs are not zero, the use of a discrete Fourier transform (DFT) to compute the frequency characteristics of the sampled signal is efficient and accurate to the level of accuracy required to enable the successful transfer of the resulting phase and frequency information to the receiver's 222 tracking module.

[00100] Figure 8 and figures 9A-9B are discussed together below. Figure 8 is a schematic diagram of a subsystem 800 for combining the results of the DFT for a plurality of time periods (for example, PRN code periods) according to a data hypothesis, according to some modalities. Figures 9A-9B illustrate the data hypothesis examples, according to some modalities. The subsystem 800 receives frequency representations 702 (for example, frequency representations 702a-702d, generated as described in relation to figure 7). For each frequency representation 702 received, subsystem 800 passes both frequency representation 702 (for example, as is) to a summation unit 802 and a negative of frequency representation 702 (for example, switches the parity of the representation frequency 702). Whether subsystem 800 passes frequency representation 702 or its negative depends on a data hypothesis that is tested.

[00101] Examples of data hypotheses are shown in figures 9A-9B. Figure 9A illustrates the possible data hypotheses for any GNSS signal with a data period longer than the four of the 602 time periods described in relation to Figure 6. For example, in some embodiments, each of the 602 time periods (figure 6) is one millisecond long. Thus, each of the frequency representations 702 (figures 7-8) is generated using a millisecond of data. The data signal can transition (for example, from a “1” value to a “0” value or a “0” value to a “1” value) after any of these millisecond periods, but, if the data (for example, for the GNSS signal that is acquired by the receiver) is longer than four milliseconds, the data signal can only transition at most once during the four milliseconds represented by the four 602a-602d time periods. Because the magnitude of the combined frequency representation 804 is what matters, one can consider, without loss of generality, that the data value for the first millisecond is a “0” value. Thus, the four hypotheses that will be tested are: no data transition, a data transition after the first millisecond, a data transition after the second millisecond, and a data transition after the third millisecond.

[00102] In some modalities, each data hypothesis is tested to produce a candidate combined frequency representation 801. In some modalities, the candidate combined frequency representation 801 with the highest magnitude is selected as the combined frequency representation 804.

[00103] Figure 9B illustrates the possible data hypotheses for a GNSS signal with a data period shorter than the four of the 602 time periods described in relation to figure 6. For example, the wide area augmentation system is a GNSS system with a data period of 2 milliseconds. In such cases, the data signal may not transition once, once or twice. In such cases, there are 5 data hypotheses that will be tested, as shown in figure 9B (note that two of the six data hypotheses (potential sampled signal patterns) shown in figure 9B are the same, resulting in 5 distinct data hypotheses. ).

[00104] Figures 10A-10B illustrate a flow chart of a method 1000 of acquiring a signal from a satellite in a global satellite navigation system (GNSS) and, more particularly, of acquiring a tracking frequency for the satellite, according to some modalities. Method 1000 is typically performed by a moving object that has a circuit system, such as a signal receiver (for example, receiver 120, figure 1) and one or more processors (for example, one or more computer system processors 130, figure 1), but, optionally, it is carried out, at least in part, by a system external to or remote from the moving object. In some embodiments, method 1000 is performed by a GNSS signal acquisition engine (for example, GNSS signal acquisition engine 316, figure 3) from a signal receiver on a moving object. For ease of explanation, method 1000 will be explained as being performed by a moving object, but it will be understood that at least some parts of method 1000 can be performed by an external system.

[00105] For each respective time period of a plurality of time periods (1002): the mobile object performs operations 1004, 1008, and 1012. In some embodiments, the time period is a period of a complete instance of the code pseudo-random. In some embodiments, operations 1004, 1008 and 1002 are performed for each of four consecutive time periods.

[00106] For this purpose, the moving object generates (1004) a plurality of samples of a signal from a satellite in a global satellite navigation system (GNSS) (for example, 8,000 samples). The signal includes a pseudo-random code for the satellite. In some circumstances, the signal includes a data signal that provides a parity for the pseudo-random code (for example, the data signal is modulated at the top of the pseudo-random code). In some embodiments, the plurality of signal samples is generated using a coarse-frequency assumption (for example, adjacent coarse-frequency assumptions that are separated by 2 kHz steps).

[00107] In some embodiments, the generation of the plurality of signal samples includes: initially sampling (1006) the signal in an initial multiple of a coarse frequency hypothesis; and decimating the signal initially sampled to produce the plurality of samples of the signal. For example, in some modalities, analog to digital converters 308 (figure 3) sample the signal at a rate of roughly 40.92 MHz, and decimator 410 discards 90% of the samples to produce a decimated signal with a sampling rate of 4.092 MHz. As discussed earlier, sample quantization can also be used to significantly reduce the required sample memory size 414.

[00108] The movable object correlates (1008) a plurality of segments of the plurality of signal samples with a local copy of the pseudo-random code for the satellite, thus producing a plurality of correlation values for the respective period of time. In some embodiments, the correlation of the plurality of segments of the plurality of signal samples with the local copy of the pseudo-random code for the satellite for each respective time period of the plurality of time periods includes (1010) correlating n segments of the plurality of samples of the signal with the local copy of the pseudo-random code, where n is an integer greater than one (for example, four segments of the plurality of samples for each time period are correlated with the local copy of the pseudo-random code, as described in relation to to figure 6).

[00109] In some embodiments, each correlated segment of the plurality of signal samples corresponds to a duration of time (for example, 250 μs, for example, a fraction of the time period, such as V of the time period). In some modalities, each segment corresponds to a quarter of the time period, in such a way that four correlation values are produced for the respective time period (for example, n = 4). In some modalities, segments are continuous segments, each corresponding to a fraction of the time period. In some embodiments, time periods are milliseconds (that is, each time period lasts for 1 millisecond, or approximately 1 millisecond).

[00110] In some modalities, the moving object performs (1012) a discrete Fourier transform (DFT) using, as inputs, the plurality of correlation values for the respective period of time, thus producing a frequency representation of the values of correlation for the respective time period. For example, the discrete Fourier transform for each respective period of time is performed separately from the discrete Fourier transform for each other respective period of time (for example, as described in relation to figure 7). In some modalities, the discrete Fourier transform for each respective period of time is performed by the same hardware as the Fourier transform for each other respective period of time (for example, in series). In some modalities, the discrete Four transform for each respective time period is performed by different hardware than the Fourier transform for each other respective time period (for example, in parallel).

[00111] In some modalities, the moving object repeats the operations of generation, correlation, realization of the DFT and combination with adjacent thick frequency hypotheses that are separated by a value less than or equal to the inverse of the time duration of each segment. For example, NCO 406 (figure 4) walks in 2 kHz steps, which is less than 1/250 μs = 4 kHz. In some modalities, the operations of generation, correlation, realization of the discrete Fourier transform and combination are performed for each of a plurality of hypotheses of coarse frequency. In some modalities, other than changing a coarse frequency hypothesis (for example, in steps greater than or equal to 500 Hz, 1 kHz, 2 kHz, or 4 kHz), the sampling frequency is not modified. For example, using the 1000 method, it is not necessary to test the fine frequency hypothesis in which the frequency hypotheses are tested in increments at the tracking limit (for example, 125 Hz).

[00112] In some modalities, the realization of the DFT for a respective period of time of the plurality of periods of time includes (1014): using, as inputs, the n correlation values for the respective period of time. The n correlation values are changed by n DFT entries compared to the n correlation values for a previous and adjacent time period of the plurality of time periods. Take, as an example, a modality in which n = 4. For the first period of time, the four correlations are applied to the first four DFT entries (for example, as shown in relation to the calculation of DFT 704a, figure 7) . The rest of the DFT entries are filled with zeros (for example, zero values are applied to the remaining entries) and the DFT is executed. For the next period of time, the four correlations are applied to the fifth to eighth DFT entries (for example, as shown in relation to the calculation of DFT 704b, figure 7). The rest of the DFT entries are filled with zeros (for example, zero values are applied to the remaining entries) and the DFT is executed.

[00113] In some modalities, the DFT is (1016) a DFT of point m, where m is an integer greater than n. For example, as described in relation to figure 7, in some modalities, the DFT is a 32-point DFT and four correlation values are used for each DFT calculation.

[00114] In some modalities, the realization of the DFT includes (1018) using, as inputs, m - n zero values in addition to the n correlation values for the respective period of time. For example, as described in relation to figure 7, in some embodiments, all entries in a DFT calculation that are not provided with a correlation value are provided with a zero value.

[00115] In some embodiments, each correlated segment of the plurality of signal samples corresponds (1020) to a duration of time (for example, 250 μs, for example, a fraction of the time period, such as V of the time period) . The plurality of signal samples is generated using a coarse frequency hypothesis. The operations of generation, correlation, realization of the DFT and combination are repeated with adjacent coarse frequency assumptions that are separated by a value less than or equal to the inverse of the time duration. In some embodiments, an inverse of the time duration divided by m is less than or equal to a frequency tolerance for tracking the satellite signal using the tracking frequency. For example, a 250 μs correlation period corresponds to the DFT which has a range of 4 kHz (1/250 μs = 4 kHz). Using a 32-point DFT implies that each point corresponds to a frequency range of 125 Hz and thus an accuracy of ± 62.5 Hz, which, in some modalities, is within the frequency tolerance for tracking the satellite signal (for example, using the crawler).

[00116] The moving object combines (1022) the frequency representations of the correlation values for the plurality of time periods according to a data hypothesis (for example, linearity that combines the frequency representations, as described in relation to the 8 and 9A-9B). In some modalities, the combination of the frequency representations of the correlation values for the plurality of time periods according to the data hypothesis includes adding the frequency representations of the correlation values with an applied parity according to the data hypothesis.

[00117] According to a determination that a magnitude of the combined frequency representations of the correlation values for the plurality of time periods meets predefined criteria (for example, the combined magnitude of the frequency position that has the maximum combined magnitude satisfies a limit predefined), the moving object (1024) selects a frequency corresponding to the magnitude as a tracking frequency for the satellite.

[00118] In some embodiments, the frequency representations of the correlation values are added for each of the possible data hypotheses (for example, the four or six data hypotheses shown in figures 9A and 9B), and the combined frequency representation with the maximum magnitude (that is, the highest combined magnitude for any of the frequency positions of the discrete Fourier transform) is selected, taking into account all possible data hypotheses.

[00119] In some modalities, the correlation operations, realization of the discrete Fourier transform and combination described above are performed for each of a plurality of code change hypotheses. For each hypothesis of code change, the maximum combined magnitude (for example, the combined frequency representation 804, figure 8) produced by operation 1022 replaces the previously computed maximum combined magnitude if it is greater than the previously computed maximum combined magnitude for all previously considered code change hypotheses (for the current frequency hypothesis).

[00120] In some modalities, for a respective frequency hypothesis, the correlation operations, realization of the discrete Fourier transform and combination are performed for each of a plurality of satellites (for example, without signal resampling), by the correlation of the sampled data stored with a locally stored (or generated) replica of the PRN code (for example, stored in the sequence memory of the PRN location 416, figure 4) for each of these satellites. In some modalities, the satellites come from different constellations. In this way, the satellite data sampled using a frequency hypothesis is tested against all applicable satellite PRN codes, and any code changes to these satellite PRN codes, before the satellite data is resampled using a next frequency hypothesis. The entire acquisition process is then repeated for a next frequency hypothesis. In some modalities, the acquisition process stops, before testing all applicable frequency assumptions, when the signals for a sufficient number of satellites (for example, four or five satellites) have been acquired, and the corresponding information is provided for the tracking module 222. In some modalities, the acquisition process runs until all applicable PRN codes have been tested for all applicable frequency assumptions, thus acquiring as many satellite signals as possible.

[00121] Similarly, in some modalities, for a given hypothesis of the PRN code, since a change of code and frequency are identified that result in the combined frequency representations of the correlation values that satisfy the predefined limit (see discussion of step 1024 supra), the signal for the corresponding satellite is considered acquired, the frequency and code change information for this satellite is passed to the tracking module 222, and all additional hypothesis tests for the PRN code corresponding to this satellite are interrupted. As a result, the amount of time required to complete the satellite signal acquisition process is reduced.

[00122] Figures 11A-11D illustrate a flowchart of a method of acquiring a signal from a satellite in a global satellite navigation system (GNSS) and, more particularly, of acquiring a code change for the satellite , according to some modalities. Method 1100 is typically performed by a moving object that has a circuit system, such as a signal receiver (for example, receiver 120, figure 1) and one or more processors (for example, one or more processors in the computer system 130, figure 1), but, optionally, it is carried out, at least in part, by a system external to or remote from the moving object. In some embodiments, method 1100 is performed by a GNSS signal acquisition engine (for example, GNSS signal acquisition engine 316, figure 3) from a signal receiver on a moving object. For ease of explanation, the 1100 method will be explained as being performed by a moving object, but it will be understood that at least some parts of the 1100 method can be performed by an external system.

[00123] The moving object samples (1102) a signal at a respective frequency (for example, 4.092 MHz, which can be a decimated frequency). The signal comes from a satellite in a global satellite navigation system (GNSS). The signal includes a pseudo-random code for the satellite that has a predefined clipping length for a complete instance of the pseudo-random code.

[00124] In some modalities, the respective frequency is (1104) an integral multiple of a frequency hypothesis (for example, a frequency hypothesis for a signal clipping frequency). For example, in some embodiments, when the signal is encoded in BPSK, the integral multiple is at least 2. In some embodiments, when the signal is encoded in BOC, the integral multiple is at least 4.

[00125] The movable object stores (1106) a first part of the signal sampled in a temporary storage, the temporary storage having a size that is less than the predefined clipping length sampled in the respective frequency. For example, when the signal is sampled at 4,092 MHz, and the pseudo-random code has a clipping length of 10,230 clips sent at a frequency of 1,023 MHz, the entire pseudo-random code will have a length of 40,920 values. In some embodiments, temporary storage stores less than 40,920 values (for example, it stores 32,736 values). In some embodiments, temporary storage has a size that is less than the clipping length for GPS-L1C and BeiDou B1C. In some embodiments, temporary storage is less than twice (or four times) the predefined clipping length sampled at the respective frequency.

[00126] For each respective code change hypothesis (1108) of a plurality of code change hypotheses, the movable object performs at least operation 1110 and, optionally, operation 1114.

[00127] For this purpose, the movable object correlates (1110) the first part of the sampled signal with a local copy of a part of the pseudo-random code (for example, as described in relation to figure 6). In some embodiments, the plurality of code change hypotheses corresponds to the displacement of the sampled signal, by displacements ranging from zero to one displacement corresponding to half the length of temporary storage, in relation to the local copy of the PRN sequence. In some modalities, the correlation of the first part of the sampled signal with the local copy of the part of the pseudo-random code for each respective code change hypothesis of the plurality of code change hypotheses comprises (1112) a first iteration of a plurality of iterations of changing temporary storage.

[00128] For example, because, in some modalities, the temporary storage has a size that is smaller than the predefined clipping length sampled in the respective frequency, in some circumstances, the temporarily stored part of the satellite signal needs to be collected , with a phase to successfully detect a code change. Each temporary storage instance that is populated in this way is considered a “temporary storage offset iteration”.

[00129] In some modalities, before the correlation of the first part of the sampled signal with the local copy of a part of the pseudo-random code, the movable object temporarily stores (1114) the local copy of the part of the pseudo-random code. In some modalities, the moving object generates the local copy of the part of the pseudo-random code.

[00130] According to a determination that the correlation of the first part of the sampled signal with the local copy of the part of the pseudo-random code for the respective code change hypothesis meets matching criteria, the moving object selects (1116) the change hypothesis code for tracking the satellite. For example, in some modalities, the code change hypothesis meets matching criteria when a value of the combined frequency representation 804 (figure 8) exceeds a limit value (for example, an absolute limit value or a limit value in relation to a calculated noise floor).

[00131] In some modalities, the moving object determines (1118) that none of the correlations arising from the plurality of code change hypotheses meet the correspondence criteria. Thus, the movable object performs a second iteration of temporary storage displacement. For this purpose, the moving object stores (1120) a second part of the signal sampled in the temporary storage (for example, the signal is collected with a phase shift, as described in relation to figure 5). The second part of the sampled signal is distinct from the first part of the sampled signal (for example, phase shifted). In some modalities, for each respective code change hypothesis of the plurality of code change hypotheses, the moving object correlates (1122) the second part of the sampled signal with the local copy of the pseudo-random code part.

[00132] As noted earlier, in some modalities, the correlation of the second part of the sampled signal with the local copy of the part of the pseudo-random code for each respective code change hypothesis of the plurality of code change hypotheses comprises (1124) a second iteration of the plurality of temporary storage change iterations.

[00133] In some modalities, the correlation of the second part of the sampled signal with the local copy of the part of the pseudo-random code is performed (1126) without temporarily restoring (for example, or regenerating) the local copy of the part of the pseudo-random code.

[00134] In some modalities, according to a determination that the correlation of the second part of the sampled signal with the local copy of the part of the pseudo-random code for the respective hypothesis of code change meets matching criteria, the movable object selects (1128) the hypothesis of code change for tracking the satellite.

[00135] In some modalities, the moving object determines (1130) whether exhaustion criteria, in relation to signal sampling using the respective frequency, have been met.

[00136] In some embodiments, the exhaustion criteria include (1134) a criterion that is met when a maximum number of iterations of changing the temporary storage has been exhausted without selecting a hypothesis of changing the code for the satellite (for example, given the length of the temporary storage and the default clipping length).

[00137] In some modalities, according to a determination that exhaustion criteria, in relation to the signal sampling using the respective frequency, were satisfied, the moving object repeats the process using a different frequency hypothesis. For this purpose, the moving object: resamples (1136) the signal at a second frequency different from the respective frequency (for example, a second coarse frequency hypothesis); stores a third part of the signal sampled at the second frequency in temporary storage; for each respective code change hypothesis of the plurality of code shift hypotheses: correlates the third part of the signal sampled in the second frequency with the local copy of the pseudo-random part of the code; and, according to a determination that the correlation of the third part of the signal sampled at the second frequency with the local copy of the part of the pseudo-random code for the respective code change hypothesis meets correspondence criteria, selects the code change hypothesis for the satellite tracking.

[00138] In some modalities, the moving object adds (1138) an offset in relation to the hypothesis of code change for tracking the satellite based, at least in part, on an offset between the first part of the sampled signal and the second part of the sampled signal. In some embodiments, the displacement is determined according to the processing time.

[00139] The moving object determines (1140) a position of the GNSS receiver using the signal acquired, at least in part, by tracking the satellite signal using the selected code change hypothesis.

[00140] In some modalities, the moving object acquires (1142) a second signal from a second satellite in a second global navigation satellite system (GNSS) distinct from the global navigation satellite system. The second signal includes a second pseudo-random code for the second satellite that has a predefined second clipping length. The temporary storage has a size that is larger than the second predefined clipping length sampled at the respective frequency. In some embodiments, the temporary storage has a size that is greater than twice (or four times) the second predefined clipping length sampled at the respective frequency.

[00141] In some modalities, for each respective code change hypothesis of the plurality of code change hypotheses, the movable object: correlates (1144) the first part of the sampled signal with a local copy of a part of the second pseudo-random code; and, according to a determination that the correlation of the first part of the sampled signal with the local copy of the part of the second pseudo-random code for the respective code change hypothesis meets the correspondence criteria, selects the code change hypothesis for tracking of the second satellite. In some modalities, the plurality of code change hypotheses corresponds to the displacement of the sampled signal in relation to the local copy of the pseudo-random part of the code using multiple successive displacements (for example, successively larger (or smaller) displacements), up to a corresponding displacement. half the length of temporary storage. In some modalities, when a code change hypothesis is successful (for example, when the matching criteria are met), the part of the pseudo-random code corresponds to a subset of the first part of the pseudo-random code. In some embodiments, when a code change hypothesis is successful, the part of the pseudo-random code corresponds to a subset of the first part of the pseudo-random code that starts in the first half of the temporary storage.

[00142] In some modalities, the moving object determines that none of the correlations of the plurality of code change hypotheses meet the matching criteria (for example, the first part of the sampled signal does not correlate with the local copy of the pseudo-random part of the code using no chance of code change). The moving object stores a second part of the sampled signal in temporary storage. The second part of the sampled signal is distinct from (for example, changed from) the first part of the sampled signal (for example, as described in relation to figure 5). For each respective code change hypothesis of the plurality of code change hypotheses, the movable object correlates the second part of the sampled signal with the local copy of a part of the pseudo-random code and, according to a determination that the correlation of the second part of the signal sampled with the local copy of the part of the pseudo-random code for the respective code change hypothesis meets matching criteria, selects the code change hypothesis for satellite tracking (for example, method 1100 is repeated with the second part of the signal sampled in the temporary storage).

[00143] In some modalities, an offset is added in the event of a successful code change, and the satellite is tracked using the hypothesis of a successful code change. For example, in some modalities, an offset based on processing time is added in the event of a code change. In addition, in some embodiments, the method includes converting the code change hypothesis successfully to a higher frequency code change hypothesis (for example, a code change hypothesis at the tracking frequency instead of at the decimated sampling that was used for satellite acquisition).

[00144] Figure 12 illustrates a flowchart for method 1200. In some embodiments, method 1200 is performed by a mobile receiver. In some modalities, the 1200 method is performed by the GNSS satellite acquisition engine from a mobile receiver. The flowchart indicates the order of certain operations used in method 1000, discussed previously in relation to figures 10A-10B, and in method 1100, discussed previously in relation to figures 11A-11D, according to some modalities. Figure 12 includes four levels of nested computing loops, with the lowest-level loop (1212-1214) to test all code change hypotheses (sometimes called code shift hypotheses) for a currently selected frequency ( 1204), currently selected PRN code (1210) and, if applicable, the currently selected part of the sampled signal (for example, for long PRN codes) (1206). Operation 1214 corresponds to the correlation operations, discrete Fourier transform (DFT) and data pattern analysis previously discussed in relation to figures, 6, 7, 8 and 9A-9B. In some modalities, operation 1214 is performed using specialized hardware, sometimes implemented in an ASIC, to enable this operation to be performed hundreds of thousands or even millions of times, for all of the frequency, the PRN code and the hypotheses of change of potentially applicable code, in a predefined short period of time, such as five seconds or less. As a result, GNSS signals from all satellites, in a particular satellite constellation (for example, GPS, or GLONASS) in view of a mobile receiver, can be acquired within this predefined period of time.

[00145] Method 1200 begins with the GNSS satellite acquisition engine being initialized (1202), for example, by loading a set of PRN codes into the sequence memory of the PRN 415 location (figure 4), definition of NCO 406 in a first frequency of the candidate frequencies, definition of the code part (if applicable) in a first code part and definition of the code change in an initial or first code change (for example, zero, corresponding to no displacement or change of the PRN sequence). In step 1204, a first or next frequency (sometimes called a frequency hypothesis) is selected. If step 1204 is reached after all of the frequency, PRN code and code change assumptions have been selected and analyzed, the GNSS satellite acquisition engine provides the information (for example, a frequency value and code change ) for a set of one or more, two or more, or typically four or more GNSS signals acquired for the receiver's GNSS satellite tracking engine (for example, tracking module 222). Alternatively, in some modalities, the acquired GNSS signals are provided to the GNSS satellite tracking engine as they are acquired, as part of operations 1214, 1212, or 1210.

[00146] In step 1206, if the constellation of satellites for which the acquisition of the GNSS satellite is being carried out has long PRN codes for which the sample memory of the GNSS satellite acquisition engine (for example, sample memory 414, figure 4) is insufficiently large to store the samples for a complete PRN period, a part of the code is selected. For shorter PRN codes, there is only one piece of code, which comprises the entire PRN code, this piece of code being "selected" by default; alternatively, step 1206 is skipped when acquiring GNSS signals that have PRN codes that are short enough that samples for a full PRN code are stored in the sample memory (e.g., sample memory 414).

[00147] After performing step 1206, if applicable, or, in other circumstances, after step 1204, method 1200 progresses to step 1208. In step 1208, the received satellite signal is sampled using the selected frequency, decimated and stored in the sample memory. If a code part has been selected (1206), samples for the currently selected code part are stored in the sample memory. Once the samples are stored in the sample memory, these samples are processed or tested for all applicable PRN code assumptions (1210) and code change assumptions (1212), to minimize the number of times satellite data need to be sampled, decimated and stored in the sample memory. In particular, a first or next PRN code is selected in step 1210, and a first or next code change is selected in step 1212, and then the sampled data is correlated (1214) with a local replica of the selected PRN code, in the selected code change, as described above with respect to figure 6, the correlation values are processed using a discrete Fourier transform, as shown above with respect to figure 7, and the resulting frequency representations are combined according to all potential data patterns, as described above in relation to figures 8 and 9A-9B, to obtain or determine the strongest combined frequency representation for the currently selected PRN code and code change (and the code part, if applicable ). In some modalities, the strongest combined frequency representation is checked at this point to determine whether it meets predefined satellite signal acquisition criteria, and, if applicable, this information is recorded and / or reported to the tracking engine. GNSS satellite (for example, immediately, or in step 1230).

[00148] Steps 1210, 1212 and 1214 are repeated until all PRN codes (1222) and code change (1220) applicable to the sampled data stored in the sample memory have been processed, after which method 1200 progresses to step 1206, for selecting a next code part if more than one code part needs to be processed, or for step 1204, where a next frequency assumption is selected. In some embodiments, the repetition of steps 1210, 1212 and 1214 is interrupted if a predefined number of satellite signals (for example, four or five) has been acquired by the GNSS satellite acquisition engine, and the method, instead, proceed directly to step 1230 to report the acquired GNSS signals to the mobile receiver's GNSS satellite tracking engine.

[00149] After steps 1210, 1212 and 1214 have been repeated until all applicable PRN codes and code changes in the sampled data stored in the sample memory have been processed, method 1200 progresses to step 1206, if applicable, to select a next piece of code, or, in other circumstances, to step 1204, to select a next frequency hypothesis. In step 1206, if all pieces of code have been processed (1224), method 1200 proceeds to step 1204 to select a next frequency hypothesis. Furthermore, after the processing of a frequency hypothesis is completed, in step 1230, all GNSS signals acquired during the processing of this frequency hypothesis are reported (for example, a change in frequency and code is reported for each signal Purchased) for the mobile receiver's GNSS satellite tracking engine. In some modalities, satellites whose GNSS signals were acquired during any of the frequency hypotheses already processed are switched by the receiver to the tracking mode, using the 222 tracking module, without waiting for the additional frequency hypotheses to be processed. In some other modalities, acquisitions of the GNSS signal are reported to the tracking module 222 only after all frequency assumptions have been processed (1226).

[00150] It will be understood that, although the terms "first", "second", etc. can be used here to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from the other. For example, a first contact can be called a second contact and, similarly, a second contact can be called a first contact, without changing the meaning of the description, as long as all occurrences of the “first contact” are renamed consistently and all the occurrences of the second contact are renamed consistently. The first contact and the second contact are both contacts, but they are not the same contact.

[00151] The terminology used here is for the purpose of describing the modalities in particular only, and is not intended to be limiting of the claims. As used in the description of the modalities and the attached claims, it is intended that the singular forms "one", "one", "o" and "a" also include plural forms, unless the context clearly indicates otherwise . It will also be understood that the term "and / or", as used herein, refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms "comprises" and / or "comprising", when used in this specification, specify the presence of declared resources, integers, steps, operations, elements, and / or components, but do not prevent the presence or addition of one or more other resources, integers, steps, operations, elements, components, and / or groups thereof.

[00152] As used herein, the term "if" can be interpreted to mean "when" or "upon" or "in response to a determination" or "according to a determination" or "in response to detection", that a preceding condition is true, depending on the context. Similarly, the phrase "if [a preceding stated condition is true]" or "if [a preceding stated condition is true]" or "when [a preceding stated condition is true]" can be interpreted to mean "by determination "or" in response to the determination "or" according to a determination "or" upon detection "or" in response to detection "that the preceding condition is true, depending on the context.

[00153] The exposed description, for the purpose of explanation, was described in relation to the specific modalities. However, the illustrative discussions presented are not intended to be exhaustive or to limit the invention to the precise forms described. Many modifications and variations are possible in view of the exposed precepts. The modalities were chosen and described in order to better explain the principles of the invention and its practical applications, in order to enable others skilled in the art to better use the invention and the various modalities with various modifications that are suitable for the particular use contemplated. .

Claims (20)

Method, characterized by the fact that it comprises:
on a Global Navigation Satellite System (GNSS) receiver that includes one or more processors and instructions for execution by one or more processors:
acquire a signal from a satellite in a global satellite navigation system (GNSS), where the signal includes a pseudo-random code for the satellite, the acquisition including:
for each respective time period of a plurality of time periods:
generating a plurality of signal samples;
correlating a plurality of segments of the plurality of signal samples with a local copy of the pseudo-random code for the satellite, thereby producing a plurality of correlation values for the respective time period;
perform a discrete Fourier transform (DFT) using, as inputs, the plurality of correlation values for the respective time period, thus producing a frequency representation of the correlation values for the time period;
combining frequency representations of correlation values for the plurality of time periods according to a data hypothesis to produce combined frequency representations of correlation values for the plurality of time periods;
according to a determination that a magnitude of the combined frequency representations of the correlation values for the plurality of time periods meets predefined criteria, select a frequency corresponding to the magnitude as a tracking frequency for the satellite; and
determine a position of the GNSS receiver using the signal acquired at least in part by tracking the satellite signal using the tracking frequency. Method according to claim 1, characterized by the fact that:
each correlated segment of the plurality of signal samples corresponds to a duration of time;
the plurality of signal samples is generated using a coarse frequency hypothesis; and
the method includes repeating the generation, correlation, DFT and combination operations with adjacent coarse frequency assumptions that are separated by a value less than or equal to the inverse of the time duration. Method according to claim 1, characterized by the fact that generating the plurality of signal samples includes:
initially sampling the signal at an initial multiple of a frequency hypothesis; and
decimate the signal initially sampled to produce the plurality of signal samples. Method according to claim 1, characterized by the fact that:
correlating the plurality of segments of the plurality of signal samples with the local copy of the pseudo-random code for the satellite for each respective time period of the plurality of time periods includes correlating n segments of the plurality of signal samples with the local copy of the pseudo-random code to produce n correlation values for each respective time period, where n is an integer greater than one;
the DFT is a DFT of point m, where m is an integer greater than n; and
performing the DFT includes using m - η zero values as inputs in addition to the correlation values n for the respective time period. Method according to claim 4, characterized by the fact that:
each correlated segment of the plurality of signal samples corresponds to a duration of time; and
an inverse of the duration of time divided by m is less than a frequency tolerance for tracking the satellite signal using the tracking frequency. Method according to claim 4, characterized by the fact that performing the DFT for a respective time period of the plurality of time periods includes:
use, as inputs, the n correction values for the respective time period, where the n correlation values are changed by n DFT entries compared to the n correlation values for a previous and adjacent time period of the plurality of periods of time. Method according to claim 1, characterized by the fact that the correlation operations, perform the discrete Fourier transform, and combination are performed for each of a plurality of code change hypotheses. Method according to claim 1, characterized by the fact that, for a respective frequency hypothesis, the correlation operations, perform the discrete Fourier transform, and combination are performed for each of a plurality of satellites. Method according to claim 1, characterized by the fact that the respective period of time is a period of a complete instance of the pseudo-random code. Global satellite navigation system (GNSS) receiver, characterized by the fact that it comprises:
one or more processors; and
memory storage instructions that, when executed by a global satellite navigation system (GNSS) receiver that includes one or more processors, make the GNSS receiver:
acquire a signal from a satellite in a global satellite navigation system, where the signal includes a pseudo-random code for the satellite, the acquisition including:
for each respective time period of a plurality of time periods:
generating a plurality of signal samples;
correlating a plurality of segments of the plurality of signal samples with a local copy of the pseudo-random code for the satellite, thereby producing a plurality of correlation values for the respective time period;
perform a discrete Fourier transform (DFT) using, as inputs, the plurality of correlation values for the respective time period, thus producing a frequency representation of the correlation values for the time period;
combining the frequency representations of the correlation values for the plurality of time periods according to a data hypothesis;
according to a determination that a magnitude of the combined frequency representations of the correlation values for the plurality of time periods meets predefined criteria, selecting a frequency corresponding to the magnitude as a tracking frequency for the satellite; and
determine a position of the GNSS receiver using the signal acquired at least in part by tracking the satellite signal using the tracking frequency. Global satellite navigation system (GNSS) receiver according to claim 10, characterized by the fact that:
each correlated segment of the plurality of signal samples corresponds to a duration of time;
the plurality of signal samples is generated using a coarse frequency hypothesis; and
the method includes repeating the generation, correlation, DFT and combination operations with adjacent coarse frequency assumptions that are separated by a value less than or equal to the inverse of the time duration. Global satellite navigation system (GNSS) receiver according to claim 10, characterized by the fact that generating the plurality of signal samples includes:
initially sampling the signal at an initial multiple of a frequency hypothesis; and
decimate the signal initially sampled to produce the plurality of signal samples. Global satellite navigation system (GNSS) receiver according to claim 10, characterized by the fact that:
correlating the plurality of segments of the plurality of signal samples with the local copy of the pseudo-random code for the satellite for each respective time period of the plurality of time periods includes correlating n segments of the plurality of signal samples with the local copy of the pseudo-random code to produce n correlation values for each respective time period, where n is an integer greater than one;
the DFT is a DFT of point m, where m is an integer greater than n; and
performing the DFT includes using m - n zero values as inputs in addition to the n correlation values for the respective time period. Global satellite navigation system (GNSS) receiver according to claim 13, characterized by the fact that:
each correlated segment of the plurality of signal samples corresponds to a duration of time; and
an inverse of the duration of time divided by m is less than a frequency tolerance for tracking the satellite signal using the tracking frequency. Global satellite navigation system (GNSS) receiver according to claim 13, characterized by the fact that carrying out the DFT for a respective time period of the plurality of time periods includes:
use, as inputs, the n correction values for the respective time period, where the n correlation values are changed by n DFT entries compared to the n correlation values for a previous and adjacent time period of the plurality of periods of time. Non-transitory computer-readable storage medium, characterized by the fact that it stores instructions that, when executed by a receiver of the Global Navigation Satellite System (GNSS) that includes one or more processors, make the GNSS receiver:
acquire a signal from a satellite in a global satellite navigation system, where the signal includes a pseudo-random code for the satellite, the acquisition including:
for each respective time period of a plurality of time periods:
generating a plurality of signal samples;
correlating a plurality of segments of the plurality of signal samples with a local copy of the pseudo-random code for the satellite, thereby producing a plurality of correlation values for the respective time period;
perform a discrete Fourier transform (DFT) using, as inputs, the plurality of correlation values for the respective time period, thus producing a frequency representation of the correlation values for the time period;
combining the frequency representations of the correlation values for the plurality of time periods according to a data hypothesis;
according to a determination that a magnitude of the combined frequency representations of the correlation values for the plurality of time periods meets predefined criteria, selecting a frequency corresponding to the magnitude as a tracking frequency for the satellite; and
determine a position of the GNSS receiver using the signal acquired at least in part by tracking the satellite signal using the tracking frequency. Non-transitory computer-readable storage medium according to claim 16, characterized by the fact that:
each correlated segment of the plurality of signal samples corresponds to a duration of time;
the plurality of signal samples is generated using a coarse frequency hypothesis; and
the method includes repeating the generation, correlation, DFT and combination operations with adjacent coarse frequency assumptions that are separated by a value less than or equal to the inverse of the time duration. Non-transitory computer-readable storage medium according to claim 16, characterized by the fact that generating the plurality of signal samples includes:
initially sampling the signal at an initial multiple of a frequency hypothesis; and
decimate the signal initially sampled to produce the plurality of signal samples. Non-transitory computer-readable storage medium according to claim 16, characterized by the fact that:
correlating the plurality of segments of the plurality of signal samples with the local copy of the pseudo-random code for the satellite for each respective time period of the plurality of time periods includes correlating n segments of the plurality of signal samples with the local copy of the pseudo-random code to produce n correlation values for each respective time period, where n is an integer greater than one;
the DFT is a DFT of point m, where m is an integer greater than n; and
performing the DFT includes using m - n zero values as inputs in addition to the n correlation values for the respective time period. Non-transitory computer-readable storage medium according to claim 19, characterized by the fact that: each correlated segment of the plurality of signal samples corresponds to a duration of time; and
an inverse of the duration of time divided by m is less than a frequency tolerance for tracking the satellite signal using the tracking frequency.

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